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This is an image search engine project using tenserflow&Flask&Pillow (University project )

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Simple Image Search Engine

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Overview

  • Simple image-based image search engine using Keras + Flask. You can launch the search engine just by running two python scripts.
  • offline.py: This script extracts a deep-feature from each database image. Each feature is a 4096D fc6 activation from a VGG16 model with ImageNet pre-trained weights.
  • server.py: This script runs a web-server. You can send your query image to the server via a Flask web-interface. The server finds similar images to the query by a simple linear scan.
  • GPUs are not required.
  • Tested on Ubuntu 18.04 and WSL2 (Ubuntu 20.04)

Usage

git clone https://github.com/matsui528/sis.git
cd sis
pip install -r requirements.txt

# Put your image files (*.jpg) on static/img

# Then fc6 features are extracted and saved on static/feature
# Note that it takes time for the first time because Keras downloads the VGG weights.
python offline.py

# Now you can do the search via localhost:5000
python server.py

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This is an image search engine project using tenserflow&Flask&Pillow (University project )

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